Results

cesm2.ssp245

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Metriclstm xgboost naive cnncnn lstm xgboost naive
diff_of_means1.026 1.534 1.575 -1.621
ratio_of_sd 0.946 0.909 0.914 0.949
amplitude_ratio_of_means 0.768 0.609 0.641 0.740
maximum_error 0.190 0.154 0.173 0.138
ks_mean_on_coarse_res_with_extremes 0.186 0.347 0.323 0.259
qqplot_mae 0.056 0.093 0.103 0.087
acf_mae 0.087 0.140 0.126 0.100
extremogram_mae 0.033 0.074 0.065 0.054
-0.838 1.370 1.534 1.575
ratio_of_sd 0.980 0.969 0.909 0.914
amplitude_ratio_of_means 0.816 0.779 0.609 0.641
maximum_error 0.208 0.148 0.154 0.173
ks_mean_on_coarse_res_with_extremes 0.196 0.179 0.347 0.323
qqplot_mae 0.048 0.058 0.093 0.103
acf_mae 0.087 0.094 0.140 0.126
extremogram_mae 0.043 0.034 0.074 0.065

Time series of the first days

Plots

Important: Right now we are only estimating the upper tail extremogram. Currently we didn’t find a way to estimate the two tales at the same time. We are using quant = .97

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>>>>>>> scaler

cesm2.ssp370

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<<<<<<< HEAD ======= >>>>>>> scaler <<<<<<< HEAD ======= >>>>>>> scaler
Metric lstm naive xgboost cnn
diff_of_means0.525 0.718 0.758 -2.057
ratio_of_sd 0.952 0.909 0.899 0.957
amplitude_ratio_of_means 0.772 0.641 0.609 0.748
maximum_error 0.198 0.174 0.152 0.145
ks_mean_on_coarse_res_with_extremes 0.142 0.245 0.324 0.194
qqplot_mae 0.057 0.115 0.106 0.105
acf_mae 0.078 0.118 0.130 0.092
0.500 0.718 0.758 -1.629
ratio_of_sd 0.962 0.909 0.899 0.978
amplitude_ratio_of_means 0.779 0.641 0.609 0.817
maximum_error 0.176 0.174 0.152 0.213
ks_mean_on_coarse_res_with_extremes 0.109 0.245 0.324 0.175
qqplot_mae 0.072 0.115 0.106 0.079
acf_mae 0.087 0.118 0.130 0.079
extremogram_mae 0.013 0.044 0.0410.023
0.015

Time series of the first days

Plots

Important: Right now we are only estimating the upper tail extremogram. Currently we didn’t find a way to estimate the two tales at the same time. We are using quant = .97

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=======

>>>>>>> scaler

cesm2.ssp585

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<<<<<<< HEAD ======= >>>>>>> scaler <<<<<<< HEAD ======= >>>>>>> scaler
Metriclstm cnncnn lstmxgboost naive
diff_of_means0.972 -1.559 1.649 1.685
ratio_of_sd 0.952 0.960 0.891 0.897
amplitude_ratio_of_means 0.783 0.763 0.610 0.643
maximum_error 0.201 0.161 0.146 0.163
ks_mean_on_coarse_res_with_extremes 0.130 0.147 0.310 0.279
qqplot_mae 0.052 0.084 0.107 0.118
acf_mae 0.068 0.082 0.122 0.111
extremogram_mae 0.038 0.045 0.071 0.066
-0.885 1.373 1.649 1.685
ratio_of_sd 0.969 0.955 0.891 0.897
amplitude_ratio_of_means 0.829 0.786 0.610 0.643
maximum_error 0.218 0.173 0.146 0.163
ks_mean_on_coarse_res_with_extremes 0.151 0.126 0.310 0.279
qqplot_mae 0.062 0.068 0.107 0.118
acf_mae 0.068 0.075 0.122 0.111
extremogram_mae 0.037 0.041 0.071 0.066

Time series of the first days

Plots

Important: Right now we are only estimating the upper tail extremogram. Currently we didn’t find a way to estimate the two tales at the same time. We are using quant = .97

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>>>>>>> scaler

ec_earth3.ssp434

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<<<<<<< HEAD ======= >>>>>>> scaler <<<<<<< HEAD ======= >>>>>>> scaler
Metriclstm cnn xgboost naivexgboost naive lstm cnn
diff_of_means0.925 -1.538 -4.327 -4.509
ratio_of_sd 0.954 0.968 0.971 0.990
amplitude_ratio_of_means 0.766 0.743 0.638 0.665
maximum_error 0.195 0.137 0.180 0.135
ks_mean_on_coarse_res_with_extremes 0.257 0.273 0.405 0.388
qqplot_mae 0.101 0.080 0.173 0.178
acf_mae 0.085 0.098 0.132 0.128
extremogram_mae 0.094 0.098 0.135 0.131
-4.327 -4.509 -4.754 -6.878
ratio_of_sd 0.971 0.990 1.029 1.055
amplitude_ratio_of_means 0.638 0.665 0.804 0.848
maximum_error 0.180 0.135 0.201 0.248
ks_mean_on_coarse_res_with_extremes 0.405 0.388 0.274 0.263
qqplot_mae 0.173 0.178 0.188 0.272
acf_mae 0.132 0.128 0.094 0.095
extremogram_mae 0.135 0.131 0.093 0.093

Time series of the first days

Plots

Important: Right now we are only estimating the upper tail extremogram. Currently we didn’t find a way to estimate the two tales at the same time. We are using quant = .97

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=======

>>>>>>> scaler

mri_esm2_0.ssp245

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<<<<<<< HEAD ======= >>>>>>> scaler <<<<<<< HEAD ======= >>>>>>> scaler
Metriclstm cnn xgboost naivecnn xgboost naive lstm
diff_of_means0.808 -1.506 36.022 36.479
ratio_of_sd 0.959 0.970 0.546 0.610
amplitude_ratio_of_means 0.764 0.750 0.368 0.522
maximum_error 0.202 0.163 0.269 0.239
ks_mean_on_coarse_res_with_extremes 0.194 0.224 0.373 0.233
qqplot_mae 0.065 0.066 1.425 1.442
acf_mae 0.083 0.097 0.128 0.084
extremogram_mae 0.030 0.036 0.045 0.026
32.753 36.022 36.479 38.667
ratio_of_sd 0.641 0.546 0.610 0.671
amplitude_ratio_of_means 0.645 0.368 0.522 0.607
maximum_error 0.166 0.269 0.239 0.196
ks_mean_on_coarse_res_with_extremes 0.062 0.373 0.233 0.040
qqplot_mae 1.295 1.425 1.442 1.529
acf_mae 0.031 0.128 0.084 0.049
extremogram_mae 0.027 0.045 0.026 0.009

Time series of the first days

Plots

Important: Right now we are only estimating the upper tail extremogram. Currently we didn’t find a way to estimate the two tales at the same time. We are using quant = .97

<<<<<<< HEAD

=======

>>>>>>> scaler

mri_esm2_0.ssp370

<<<<<<< HEAD
<<<<<<< HEAD ======= >>>>>>> scaler <<<<<<< HEAD ======= >>>>>>> scaler
Metriclstm cnn xgboost naivecnn xgboost naive lstm
diff_of_means0.909 -1.383 36.673 37.285
ratio_of_sd 0.949 0.960 0.529 0.599
amplitude_ratio_of_means 0.769 0.756 0.361 0.526
maximum_error 0.183 0.156 0.273 0.213
ks_mean_on_coarse_res_with_extremes 0.144 0.183 0.323 0.204
qqplot_mae 0.057 0.073 1.451 1.474
acf_mae 0.065 0.079 0.115 0.067
extremogram_mae 0.011 0.017 0.032 0.019
33.020 36.673 37.285 39.359
ratio_of_sd 0.631 0.529 0.599 0.658
amplitude_ratio_of_means 0.647 0.361 0.526 0.604
maximum_error 0.177 0.273 0.213 0.225
ks_mean_on_coarse_res_with_extremes 0.043 0.323 0.204 0.102
qqplot_mae 1.305 1.451 1.474 1.556
acf_mae 0.045 0.115 0.067 0.040
extremogram_mae 0.030 0.032 0.019 0.028

Time series of the first days

Plots

Important: Right now we are only estimating the upper tail extremogram. Currently we didn’t find a way to estimate the two tales at the same time. We are using quant = .97

<<<<<<< HEAD

=======

>>>>>>> scaler

mri_esm2_0.ssp434

<<<<<<< HEAD
<<<<<<< HEAD ======= >>>>>>> scaler <<<<<<< HEAD ======= >>>>>>> scaler
Metriclstm cnn xgboost naivecnn xgboost naive lstm
diff_of_means0.433 -1.964 35.896 36.372
ratio_of_sd 0.948 0.954 0.543 0.607
amplitude_ratio_of_means 0.767 0.748 0.371 0.525
maximum_error 0.205 0.151 0.278 0.227
ks_mean_on_coarse_res_with_extremes 0.170 0.189 0.357 0.221
qqplot_mae 0.061 0.090 1.420 1.438
acf_mae 0.078 0.094 0.125 0.084
extremogram_mae 0.014 0.014 0.027 0.027
32.468 35.896 36.372 38.496
ratio_of_sd 0.646 0.543 0.607 0.674
amplitude_ratio_of_means 0.657 0.371 0.525 0.624
maximum_error 0.161 0.278 0.227 0.217
ks_mean_on_coarse_res_with_extremes 0.074 0.357 0.221 0.089
qqplot_mae 1.284 1.420 1.438 1.522
acf_mae 0.043 0.125 0.084 0.047
extremogram_mae 0.052 0.027 0.027 0.036

Time series of the first days

Plots

Important: Right now we are only estimating the upper tail extremogram. Currently we didn’t find a way to estimate the two tales at the same time. We are using quant = .97

<<<<<<< HEAD

=======

>>>>>>> scaler